Expectation of a Random Variable

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  • #1
Firepanda
430
0
I know the E[X] = Integral between [-inf,inf] of X*f(x) dx

Where X is normally distributed and f(x) is the PDF

How do I find the expectation of X4?

Bare with me because I'm useless in Latex

So far what I've done is written the integral as Integral between [-inf,inf] of X4*f(x) dx

and I started to subsitute u = exp{-x2/2t}

So now I have Integral between [-inf,inf] of -tX3*u dx

I really don't think this is correct.. I'm trying to follow the same way my lecturer did it for the expectation of X2, but at that statge he started to integrate by parts, yet mine doesn't look like that and it's essentially the same!

Can anyone help?

Thanks
 
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  • #2
Firepanda said:
I know the E[X] = Integral between [-inf,inf] of X*f(x) dx

Where X is normally distributed and f(x) is the PDF

How do I find the expectation of X4?

Bare with me because I'm useless in Latex

So far what I've done is written the integral as Integral between [-inf,inf] of X4*f(x) dx

and I started to subsitute u = exp{-x2/2t}

So now I have Integral between [-inf,inf] of -tX3*u dx

I really don't think this is correct.. I'm trying to follow the same way my lecturer did it for the expectation of X2, but at that statge he started to integrate by parts, yet mine doesn't look like that and it's essentially the same!

Can anyone help?

Thanks

The standard way of dealing with this type of problem is to note that [itex]d\left(e^{-x^2/2}\right) = - x e^{-x^2/2} \, dx, [/itex] and use that in integration by parts.

RGV
 

1. What is the definition of "Expectation of a Random Variable"?

The expectation of a random variable is a measure of the central tendency or average value of the possible outcomes of a random experiment or process. It represents the long-term average value that would be obtained if the experiment or process were repeated many times.

2. How is the expectation of a random variable calculated?

The expectation of a random variable is calculated by multiplying each possible outcome by its probability and summing all of these products. This can be represented mathematically as E[X] = ∑xP(X=x), where X is the random variable and P(X=x) is the probability of obtaining the value x.

3. What is the significance of the expectation of a random variable?

The expectation of a random variable is an important concept in probability and statistics because it provides a single numerical value that summarizes the distribution of a random variable. It is also used in decision making and risk analysis to evaluate the potential outcomes of different scenarios.

4. Can the expectation of a random variable be negative?

Yes, the expectation of a random variable can be negative. This means that on average, the outcomes of the random variable are below zero. For example, if the random variable represents the profit of a business, a negative expectation would indicate that the business is losing money on average.

5. How does the expectation of a random variable relate to the variance and standard deviation?

The expectation of a random variable is related to the variance and standard deviation by the following equations: Var(X) = E[(X-E[X])^2] and σ = √Var(X). In other words, the variance and standard deviation measure the spread or variability of the random variable around its expected value.

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